JP5321499B2 - Signal acquisition method - Google Patents

Abstract

A signal acquisition method includes: performing a correlation operation for a satellite signal received from a positioning satellite; frequency-analyzing a result of the correlation operation over a predetermined time which is equal to or longer than a bit length of navigation message data carried by the satellite signal; extracting a power value in a predetermined frequency which includes at least a specific frequency determined according to the bit length, from a result of the frequency analysis; and acquiring the satellite signal using the extracted power value.

Description

The present invention relates to a signal acquisition method.

  A GPS (Global Positioning System) is widely known as a positioning system using positioning signals, and is used in a position calculation device built in a mobile phone or a car navigation device. In the GPS, position calculation calculation for obtaining position coordinates and clock error of the position calculation device is performed based on information such as positions of a plurality of GPS satellites and pseudo distances from each GPS satellite to the position calculation device.

  A GPS satellite signal transmitted from a GPS satellite is modulated with a spreading code different for each GPS satellite called a CA (Coarse and Acquisition) code. In order to capture a GPS satellite signal from a weak received signal, the position calculation device performs a correlation operation between the received signal and a replica CA code that is a replica of the CA code, and based on the correlation value, the GPS satellite signal To capture. In this case, in order to facilitate the detection of the peak of the correlation value, a technique of integrating the correlation value acquired by the correlation calculation over a predetermined integration time is used.

  However, since the CA code itself for spreading and modulating the GPS satellite signal is BPSK (Binary Phase Shift Keying) modulated every 20 milliseconds by the navigation message data, the polarity of the CA code is inverted every 20 milliseconds which is the bit length. Can do. Therefore, when the correlation values are integrated across the timing at which the bit value of the navigation message data changes, there is a possibility that correlation values having different signs are integrated. As a technique for solving this problem, for example, as disclosed in Patent Document 1, a technique is known in which correlation values are accumulated using assist data regarding timing at which the bit value of navigation message data changes. Yes.

JP 2001-349935 A

  According to the technique of Patent Document 1, the correlation integration time can be set longer than the bit length (20 milliseconds) of the navigation message data. However, in the technique of Patent Document 1, it is necessary to acquire assist data about the timing at which the bit value of the navigation message data changes from the outside. Therefore, there are limitations and problems related to data acquisition such as communication costs and communication time problems. It was. In particular, after the navigation message data transmitted from the GPS satellite signal is switched to new data, it becomes necessary to wait for the assist data to be updated and acquire the new assist data.

  The present invention has been made in view of the above-mentioned problems, and its object is to propose a new technique for enabling correlation processing over a correlation integration time longer than the bit length of navigation message data. There is to do.

  The first mode for solving the above problems is to perform a correlation operation on a received signal received from a satellite signal transmitted from a positioning satellite, and to calculate navigation message data carried by the satellite signal. Analyzing the correlation calculation result over a predetermined time longer than the bit length, and extracting a power value at a predetermined frequency including at least a specific frequency determined according to the bit length from the frequency analysis result And capturing the satellite signal using the extracted power value.

  As another form, a correlation operation unit that performs a correlation operation on a received signal received by the reception unit from a satellite signal for positioning, and a bit length greater than or equal to a bit length of navigation message data carried by the satellite signal An analysis unit for analyzing the frequency of the result of the correlation calculation over a predetermined time; and an extraction unit for extracting a power value at a predetermined frequency including at least a specific frequency determined according to the predetermined time among the results of the frequency analysis; A signal capturing device including a capturing unit that captures the satellite signal using the extracted power value may be configured.

  According to the first embodiment and the like, the correlation calculation is performed on the received signal received from the satellite signal transmitted from the positioning satellite. Then, frequency analysis is performed on the result of correlation calculation over a predetermined time that is equal to or greater than the bit length of the navigation message data carried by the satellite signal, and the identification determined according to the bit length of the navigation message data among the results of the frequency analysis. A power value at a predetermined frequency including at least the frequency is extracted. Then, the satellite signal is captured using the extracted power value.

  When a correlation operation is performed on a satellite signal carrying navigation message data, time-series data of correlation values having a code change is obtained. Therefore, when frequency analysis is performed on time-series data of correlation values, a peak of power value usually appears at a specific frequency determined according to the bit length of navigation message data. The peak of the specific frequency is caused by the bit length of the navigation message data, and appears when the correlation process is performed over an arbitrary time longer than the bit length. Therefore, if a power value at a specific frequency is used, correlation processing over a correlation integration time longer than the bit length at which the bit value of navigation message data can change is possible.

  Further, as a second mode, the signal acquisition method of the first mode further includes multiplying the result of the correlation calculation over the predetermined time by n (n> 1), and the frequency analysis includes the step of You may comprise the signal acquisition method which is performed with respect to the result of the said correlation calculation multiplied by n.

  According to the second embodiment, the result of the correlation calculation over a predetermined time is multiplied by n to increase the result of the correlation calculation. Then, frequency analysis is performed on the result of the n-fold correlation calculation. Thereby, the power spectral density obtained by frequency analysis can be increased.

  Further, as a third form, in the signal capturing method of the first or second form, the extraction is performed by extracting the power value at the specific frequency and a harmonic of the specific frequency. A signal capturing method may be configured.

  According to this 3rd form, the power value in a specific frequency and a harmonic of a specific frequency is extracted. When frequency analysis is performed on the correlation calculation result, a peak of the power value appears at the harmonic frequency of the specific frequency in addition to the specific frequency. Therefore, in addition to the power value at a specific frequency that is a frequency corresponding to the modulation period of the navigation message data, the power value at the harmonic of the specific frequency is also used in combination to capture satellite signals more accurately and quickly. It becomes possible to do.

  Further, as a fourth mode, the signal capturing method according to any one of the first to third modes, wherein capturing the satellite signal regards the extracted power value as a power value at a frequency of zero. A signal acquisition method including performing the acquisition may be configured.

  According to the fourth embodiment, satellite signals are captured by regarding the extracted power value as a power value at a frequency of zero. Considering the extracted power value as the power value at the frequency of zero means that the frequency analysis has resulted in a peak of the power value at the frequency of zero. The fact that there is a peak of the power value at the frequency of zero corresponds to the successful detection of the reception frequency of the satellite signal. Therefore, with this fourth embodiment, it is possible to easily determine whether or not the signal is captured.

  Further, as a fifth mode, the signal capturing method according to any one of the first to fourth modes, wherein capturing the satellite signal includes performing an inverse frequency analysis and obtaining a result of the inverse frequency analysis. And acquiring the satellite signal to form a signal acquisition method.

  As frequency analysis in the first to fifth embodiments, frequency analysis using Fourier transform may be applied as in the sixth embodiment, and wavelet transform may be performed as in the seventh embodiment. The frequency analysis used may be applied.

(A) is an example of a time change of the correlation value. (B) is an example of a frequency analysis result. (C) is explanatory drawing of the process with respect to a power value. (D) is an example of the time change of the reconstructed correlation value. (A) and (B) are DC components of the correlation value. (C) is a specific frequency component of the correlation value. The block diagram which shows an example of a function structure of a portable telephone. The block diagram which shows an example of the circuit structure of a baseband process circuit part. The flowchart which shows the flow of a baseband process. The flowchart which shows the flow of a 1st correlation process. The flowchart which shows the flow of a 2nd correlation process. The flowchart which shows the flow of a 3rd correlation process. The flowchart which shows the flow of a 4th correlation process. The figure which shows an example of the correlation processing result of the phase direction in the past, and a frequency direction. The figure which shows an example of the correlation processing result of the frequency direction in the past. The figure which shows an example of the correlation processing result of the phase direction in the past. The figure which shows an example of the correlation processing result of a phase direction and a frequency direction in 1st Example. The figure which shows an example of the correlation process result of the frequency direction in 1st Example. The figure which shows an example of the correlation process result of the phase direction in 1st Example. The flowchart which shows the flow of a 5th correlation process. The flowchart which shows the flow of a 6th correlation process. The figure which shows an example of the time series change of the correlation value in the past. The figure which shows an example of the time series change of the correlation value in 2nd Example.

1. Principle First, the principle of satellite signal acquisition in this embodiment will be described.
In a position calculation system using GPS satellites, a GPS satellite, which is a type of positioning satellite, places navigation message data including satellite orbit data such as almanac and ephemeris on a GPS satellite signal, which is a type of positioning satellite signal. Outgoing.

  The GPS satellite signal is a 1.57542 [GHz] communication signal modulated by a CDMA (Code Division Multiple Access) system known as a spread spectrum system by a CA (Coarse and Acquisition) code which is a kind of spreading code. The CA code is a pseudo-random noise code having a repetition period of 1 ms with a code length of 1023 chips as one PN frame, and is different for each satellite.

  The frequency at which a GPS satellite transmits a GPS satellite signal (specified carrier frequency) is specified in advance as 1.57542 [GHz]. However, due to the influence of Doppler caused by the movement of the GPS satellite and the GPS receiver, the GPS The frequency at which the receiving device receives the GPS satellite signal does not necessarily match the specified carrier frequency. Therefore, the conventional GPS receiver captures a GPS satellite signal by performing a frequency search that is a correlation calculation in the frequency direction for capturing a GPS satellite signal from the received signal. In addition, in order to specify the phase of the received GPS satellite signal (CA code), the GPS receiving device performs a phase search that is a correlation calculation in the phase direction to capture the GPS satellite signal.

  However, particularly in a weak electric field environment such as an indoor environment, the level of the correlation value at the true reception frequency and the true code phase is low, so that it is difficult to distinguish it from noise. As a result, it is difficult to detect the true reception frequency and the true code phase, that is, to acquire the signal. Therefore, under such a reception environment, the correlation value obtained by the correlation calculation is accumulated over a predetermined correlation accumulation time, and a peak is detected from the accumulated correlation value, thereby obtaining the GPS satellite signal. A capture technique is used.

  However, the GPS satellite signal is spread and modulated by the CA code, and the CA code itself is BPSK (Binary Phase Shift Keying) modulated according to the bit value of the navigation message data. Since the bit length of the navigation message data is 20 milliseconds, the bit value may change (invert) every 20 milliseconds. The possibility means that the bit value may not change. In the present embodiment, the timing at which the bit value of the navigation message data actually changes is referred to as “bit inversion timing”.

  Changing the bit value of the navigation message data means that the polarity of the CA code is reversed. Therefore, when the correlation calculation between the received CA code and the replica code is performed, correlation values having different codes can be calculated every 20 milliseconds that is the bit length of the navigation message data. Therefore, if the correlation values are accumulated across the bit inversion timing of the navigation message data, the correlation values with different signs cancel each other, resulting in a small correlation value (0 in an extreme case). There's a problem. In order to solve this problem, the inventor of the present application has devised a new method for integrating the correlation values by aligning the signs using frequency analysis for the correlation values.

1 and 2 are diagrams for explaining the flow of correlation processing in the present embodiment.
FIG. 1A shows an example of time-series changes in correlation values. In order to make the explanation easy to understand, the correlation value is expressed by two positive and negative values of “+1” and “−1”. Here, a case will be described in which the true value of the reception frequency is known and the correlation value is obtained by performing the correlation calculation using the replica code whose phase exactly matches the reception CA code.

  When the polarity of the CA code when the bit value of the navigation message data is “1” is “positive”, the correlation value “+1” is obtained by multiplying the received CA code by the replica code. On the other hand, when the polarity of the CA code when the bit value of the navigation message data is “0” is “negative”, the correlation value “−1” is obtained by multiplying the received CA code by the replica code.

  As can be seen from FIG. 1A, the sign of the correlation value is switched at the bit inversion timing of the navigation message data. Depending on the bit value, when the bit inversion timing comes 20 milliseconds after the previous bit inversion timing, the sign of the correlation value is reversed at the time 20 minutes later. In addition, when the bit inversion timing comes after 40 milliseconds, the sign of the correlation value is reversed at the time after the 40 milliseconds.

  When the time-series correlation values shown in FIG. 1A are accumulated for a predetermined time longer than the bit length and the frequency analysis is performed, for example, a power spectrum as shown in FIG. 1B is obtained. As will be described later in the embodiment, for example, Fourier transform or wavelet transform can be applied as frequency analysis. In FIG. 1B, the horizontal axis indicates the frequency and the vertical axis indicates the power value, and the white noise is not shown for easy understanding.

  As shown in FIG. 1B, a power value peak appears at a frequency of zero (0 Hz). This indicates the DC component of the time-series correlation value. That is, as shown in FIGS. 2 (A) and 2 (B), a frequency component (DC component) corresponding to a portion having no sign change in the time-series correlation value appears as a peak of the power value of 0 Hz. It is.

  However, as shown in FIG. 1B, a peak with a large power value appears at a frequency of 25 Hz. This is due to the fact that the bit length of the navigation message data is 20 milliseconds. That is, as shown in FIG. 2C, when the bit value of the navigation message data changes every 20 milliseconds, for example, the first 20 milliseconds is “1”, the next 20 milliseconds is “−1”, Since the correlation value changes such that the next 20 milliseconds is “1”, the period of the correlation value is 40 milliseconds.

This period of 40 milliseconds is a period corresponding to twice the bit length of the navigation message data. When the period of 40 milliseconds is converted into a frequency, “f = 1 / T = 1 / (40 × 10 ⁻³ ) = 25 Hz”. This 25 Hz frequency component included in the time-series correlation value appears as a peak of the power value. In the present embodiment, the frequency of 25 Hz is defined as “specific frequency”.

  Moreover, when FIG. 1 (B) is seen, although it is not as large a peak as a specific frequency (25 Hz) also in the high-order frequencies, such as 75 Hz, 125 Hz, and 175 Hz, it turns out that the minute peak has appeared. Since the waveform of the correlation value is a symmetric waveform, a peak of the power value appears at a frequency that is an odd multiple of the specific frequency that is the fundamental frequency, that is, an odd-order harmonic frequency.

  The peak of the power value at the specific frequency originates from the fact that the polarity of the CA code is inverted at the bit inversion timing of the navigation message data and the sign of the correlation value is changed. For example, when frequency analysis is performed with the integration time of the correlation value being less than 20 milliseconds of the bit length so as not to cross the bit inversion timing, a peak occurs only at the frequency zero, and the peak is not generated at the specific frequency. Does not occur. That is, if there is no sign change of the correlation value, the power value peak at the specific frequency does not occur. Considering this in reverse, if the peak at the specific frequency can be eliminated, the change in the sign of the correlation value can be ignored, and the influence of the bit inversion of the navigation message data can be nullified.

  Therefore, in the present embodiment, as shown in FIG. 1C, the power value at the specific frequency and its harmonics (an odd multiple of the specific frequency) is added to the power value at the frequency zero (0 Hz) and A process of setting the power value at the frequency and its harmonics to 0 is performed. After performing such processing, inverse frequency analysis is performed to reconstruct time-series correlation values.

  Then, a time-series correlation value having no sign change as shown in FIG. If the correlation values having no sign change are integrated, the correlation values cancel each other and the integrated correlation value does not decrease. Therefore, by performing the above-described correlation processing, the correlation integration time can be set longer than 20 milliseconds, which is the bit length of the navigation message data, and the correlation value can be integrated at any correlation integration time. Become.

  In addition, in FIG.1 (C), although demonstrated so that the power value in a specific frequency and its harmonic may be added to the power value in frequency zero (0 Hz), the power value in the harmonic of a specific frequency is not added, Only power values at a specific frequency may be added. This is because the harmonic power value is generally lower than the power value of the specific frequency.

2. Embodiment Next, an embodiment in which the present invention is applied to a mobile phone which is a kind of electronic equipment including a satellite signal capturing device and a position calculating device will be described. Needless to say, the embodiments to which the present invention is applicable are not limited to the embodiments described below.

  FIG. 3 is a block diagram illustrating an example of a functional configuration of the mobile phone 1 common to the embodiments. The mobile phone 1 includes a GPS antenna 5, a GPS receiving unit 10, a host CPU (Central Processing Unit) 30, an operation unit 40, a display unit 50, a mobile phone antenna 60, and a mobile phone radio communication circuit. Unit 70 and storage unit 80.

  The GPS antenna 5 is an antenna that receives an RF (Radio Frequency) signal including a GPS satellite signal transmitted from a GPS satellite, and outputs a received signal to the GPS receiver 10.

  The GPS receiving unit 10 is a position calculating circuit or a position calculating device that measures the position of the mobile phone 1 based on a signal output from the GPS antenna 5, and is a functional block corresponding to a so-called GPS receiving device. The GPS receiving unit 10 includes an RF receiving circuit unit 11 and a baseband processing circuit unit 20. The RF receiving circuit unit 11 and the baseband processing circuit unit 20 can be manufactured as separate LSIs (Large Scale Integration) or can be manufactured as one chip.

  The RF receiving circuit unit 11 is an RF signal receiving circuit. As a circuit configuration, for example, a receiving circuit that converts an RF signal output from the GPS antenna 5 into a digital signal by an A / D converter and processes the digital signal may be configured. Alternatively, the RF signal output from the GPS antenna 5 may be processed as an analog signal and finally A / D converted to output a digital signal to the baseband processing circuit unit 20.

  In the latter case, for example, the RF receiving circuit unit 11 can be configured as follows. That is, an oscillation signal for RF signal multiplication is generated by dividing or multiplying a predetermined oscillation signal. Then, by multiplying the generated oscillation signal by the RF signal output from the GPS antenna 5, the RF signal is down-converted to an intermediate frequency signal (hereinafter referred to as an "IF (Intermediate Frequency) signal"), After the IF signal is amplified, it is converted into a digital signal by an A / D converter and output to the baseband processing circuit unit 20.

  The baseband processing circuit unit 20 performs correlation processing or the like on the reception signal output from the RF reception circuit unit 11 to capture a GPS satellite signal, and based on satellite orbit data, time data, and the like extracted from the GPS satellite signal. The circuit unit calculates the position (position coordinates) of the mobile phone 1 by performing a predetermined position calculation calculation. The baseband processing circuit unit 20 also functions as a satellite signal capturing device that captures GPS satellite signals from received signals.

  FIG. 4 is a diagram illustrating an example of a circuit configuration of the baseband processing circuit unit 20, and is a diagram mainly illustrating circuit blocks according to the present embodiment. The baseband processing circuit unit 20 includes, for example, a multiplier 21, a carrier removal signal generation unit 22, a correlator 23, a replica code generation unit 24, a processing unit 25, and a storage unit 27. The

  The multiplier 21 is a multiplier that removes a carrier wave from the received signal by multiplying the received signal by the carrier removing signal generated and generated by the carrier removing signal generator 22 and outputs the carrier signal to the correlator 23. is there.

  The carrier removal signal generator 22 is a circuit that generates a carrier removal signal that is a signal having the same frequency as the carrier signal of the GPS satellite signal, and includes an oscillator such as a carrier NCO (Numerical Controlled Oscillator). Is done. When the signal output from the RF receiving circuit unit 11 is an IF signal, the signal is generated using the IF frequency as a carrier frequency. In any case, this is a circuit for generating a carrier removal signal having the same frequency as that of the signal output from the RF receiving circuit unit 11.

  The correlator 23 is a correlator that performs a correlation operation between the generation signal of the replica code generated by the replica code generation unit 24 and the reception signal from which the carrier output from the multiplier 21 is removed, and corresponds to the correlation calculation unit. To do.

  The replica code generating unit 24 is a circuit unit that generates a replica code of a CA code that is a spreading code of a GPS satellite signal, and includes an oscillator such as a code NCO. The replica code generation unit 24 generates a replica code corresponding to the PRN number (satellite number) instructed from the processing unit 25 by adjusting the output phase (time) according to the instructed phase, and sends it to the correlator 23. Output.

  The correlator 23 performs correlation processing on each IQ component of the received signal with the replica code input from the replica code generation unit 24. The I component indicates the in-phase component (real part) of the received signal, and the Q component indicates the quadrature component (imaginary part) of the received signal.

  In addition, although illustration is abbreviate | omitted about the circuit block which isolate | separates IQ component (IQ isolation | separation) of a received signal, you may comprise a circuit block how. For example, when the received signal is down-converted to an IF signal in the RF receiving circuit unit 11, IQ separation may be performed by multiplying the received signal by a local oscillation signal having a phase difference of 90 degrees.

  The processing unit 25 is a control device that comprehensively controls each functional unit of the baseband processing circuit unit 20, and includes a processor such as a CPU, for example. The processing unit 25 functions as an analysis unit that performs frequency analysis on the result of the correlation calculation output from the correlator 23, and also includes an extraction unit that extracts a power value at a specific frequency and a harmonic frequency from the frequency analysis result, It functions as a capturing unit that captures a GPS satellite signal from the signal. The processing unit 25 includes a satellite signal acquisition unit 251 and a position calculation unit 253 as main functional units.

  The satellite signal acquisition unit 251 performs processing for integrating the correlation value output from the correlator 23 over the correlation integration time, and acquires the GPS satellite signal based on the integrated correlation value (integrated correlation value).

  The position calculation unit 253 is a calculation unit that performs a known position calculation calculation using the GPS satellite signal captured by the satellite signal capturing unit 251 to calculate the position of the mobile phone 1. It outputs to CPU30.

  The storage unit 27 is configured by a storage device (memory) such as a ROM (Read Only Memory), a flash ROM, or a RAM (Random Access Memory), and the system program of the baseband processing circuit unit 20, the satellite signal capturing function, and the position calculation. Various programs, data, and the like for realizing various functions such as functions are stored. In addition, it has a work area for temporarily storing data being processed and results of various processes.

  For example, as illustrated in FIG. 4, the storage unit 27 stores a baseband processing program 271 that is read as a program by the processing unit 25 and executed as baseband processing (see FIG. 5). The baseband processing program 271 has a correlation processing program 2711 executed as various types of correlation processing (see FIGS. 6 to 9, FIG. 16 and FIG. 17) as a subroutine.

  Further, as temporarily stored data, for example, satellite orbit data 272, correlation integration time 273, accumulation time 274, correlation value data 275, increased correlation value data 276, integration correlation value data 277, specific frequency 278 and the harmonic frequency 279 are stored in the storage unit 27.

  In the baseband processing, the processing unit 25 performs various correlation processes for each GPS satellite to be captured (hereinafter referred to as “capture target satellite”) to capture a GPS satellite signal, and captures it. This is a process for calculating the position of the mobile phone 1 by performing position calculation using the GPS satellite signal.

  In addition, the correlation processing means that the processing unit 25 performs frequency analysis on a time-series correlation value according to the principle described above, considers a power value at a specific frequency or a harmonic frequency as a power value at frequency zero, and performs inverse frequency analysis. This is processing for reconstructing time-series correlation values. The integrated correlation value is acquired by integrating the reconstructed time-series correlation values. These processes will be described later in detail using a flowchart.

  The satellite orbit data 272 is data such as an almanac that stores approximate satellite orbit information of all GPS satellites, and an ephemeris that stores detailed satellite orbit information for each GPS satellite. The satellite orbit data 272 is obtained by decoding GPS satellite signals received from GPS satellites, and is obtained as assist data from, for example, the base station of the mobile phone 1 or an assist server.

  The correlation integration time 273 is a time for integrating the correlation values accumulated for each accumulation time 274, and is variably set based on information such as the signal strength of the reception signal and the reception environment. The accumulation time 274 is a time for accumulating the correlation value output from the correlator 23, and is set, for example, as a time 1 / m times (m> 1) the correlation integration time 273.

  The correlation value data 275 is data in which the correlation value output from the correlator 23 is accumulated for the accumulation time 274. The increased correlation value data 276 is data of an increased correlation value obtained by multiplying the correlation value for the accumulation time by n (n> 1). In the present embodiment, frequency analysis is performed on the increased correlation value data 276 in order to increase the power spectral density obtained by frequency analysis.

  The integrated correlation value data 277 is integrated correlation value data obtained by integrating the correlation values reconstructed by inverse frequency analysis.

  The specific frequency 278 is a frequency determined according to the bit length of the navigation message data. In the present embodiment, as described in the principle, 25 Hz, which is a correlation value period of 40 milliseconds corresponding to twice the bit length, is converted into a frequency. Further, the harmonic frequency 279 is a harmonic frequency that is an odd multiple of the specific frequency 278.

  Returning to the functional blocks in FIG. 3, the host CPU 30 is a processor that comprehensively controls each unit of the mobile phone 1 according to various programs such as a system program stored in the storage unit 80. Based on the position coordinates output from the baseband processing circuit unit 20, the host CPU 30 displays a map indicating the current position on the display unit 50, or uses the position coordinates for various application processes.

  The operation unit 40 is an input device configured by, for example, a touch panel, a button switch, or the like, and outputs a pressed key or button signal to the host CPU 30. By operating the operation unit 40, various instructions such as a call request, a mail transmission / reception request, and a position calculation request are input.

  The display unit 50 is configured by an LCD (Liquid Crystal Display) or the like, and is a display device that performs various displays based on display signals input from the host CPU 30. The display unit 50 displays a position display screen, time information, and the like.

  The cellular phone antenna 60 is an antenna that transmits and receives cellular phone radio signals to and from a radio base station installed by a communication service provider of the cellular phone 1.

  The cellular phone wireless communication circuit unit 70 is a cellular phone communication circuit unit configured by an RF conversion circuit, a baseband processing circuit, and the like, and performs modulation and demodulation of the cellular phone radio signal, thereby enabling communication and mailing. Realize transmission / reception of

  The storage unit 80 is a storage device that stores a system program for the host CPU 30 to control the mobile phone 1 and various programs and data for executing various application processes.

2-1. First Embodiment In the first embodiment, a GPS satellite signal is captured based on an accumulated correlation value obtained by performing correlation processing using Fourier transform, which is a kind of frequency analysis, and accumulating the reconstructed correlation values. This is an example.

(1) Processing Flow FIG. 5 shows a flow of baseband processing executed in the baseband processing circuit unit 20 when the baseband processing program 271 stored in the storage unit 27 is read by the processing unit 25. It is a flowchart.

  First, the satellite signal acquisition unit 251 performs acquisition target satellite determination processing (step A1). Specifically, a GPS satellite located in the sky at a given reference position at a current time measured by a clock unit (not shown) is used as a satellite orbit data 272 such as an almanac or an ephemeris stored in the storage unit 27. To determine the satellite to be captured. For example, in the case of the first position calculation after power-on, the reference position is a position acquired from the assist server by so-called server assist, and in the second and subsequent position calculation, the reference position is the latest calculated position. Can be set.

  Next, the satellite signal acquisition unit 251 executes the process of loop A for each acquisition target satellite determined in step A1 (steps A3 to A17). In the process of loop A, the satellite signal acquisition unit 251 sets the correlation integration time 273 and the accumulation time 274 for the acquisition target satellite (step A5).

  The setting of the correlation integration time can be realized by various methods. For example, it is good also as setting based on the signal strength of the received signal from the said acquisition object satellite. The weaker the signal strength, the more difficult it is to detect the correlation value peak unless the correlation values are integrated over a longer period of time. Therefore, it is appropriate to set the correlation integration time so that the correlation integration time becomes longer as the signal strength becomes weaker.

  Further, the reception environment of the GPS satellite signal may be determined, and the correlation integration time may be determined based on the determined reception environment. For example, when the reception environment is “indoor environment (indoor environment)”, the correlation integration time is set to a longer “1000 milliseconds”, and when the reception environment is “outdoor environment (outdoor environment)”, the correlation It is conceivable to set the accumulated time to “200 milliseconds”, which is a little shorter.

  The accumulation time is set so that the correlation integration time is an integral multiple of the accumulation time. That is, the accumulation time is set to 1 / m times the correlation integration time (m> 1). The value of “m” can be set as appropriate. For example, when the correlation integration time is set to “1000 milliseconds” and “m = 25”, “40 milliseconds” is set as the accumulation time.

  Next, the satellite signal acquisition unit 251 sets the initial phase of the replica code (step A7). Then, an instruction signal indicating the PRN number of the acquisition target satellite and the phase of the replica code is output to the replica code generation unit 24 (step A9). Then, the satellite signal acquisition unit 251 performs the correlation process by reading and executing the correlation processing program 2711 stored in the storage unit 27 (step A11).

FIG. 6 is a flowchart showing the flow of the first correlation process which is an example of the correlation process.
First, the satellite signal acquisition unit 251 sets the specific frequency 278 and stores it in the storage unit 27 (step B1). As described in the principle, the specific frequency 278 is set to “25 Hz”, which is a frequency corresponding to one period, with “40 milliseconds” being a period twice the bit length of the navigation message data as one period. .

  Thereafter, the satellite signal acquisition unit 251 stores the data accumulated in the correlation value output from the correlator 23 for the accumulation time set in step A5 in the storage unit 27 as the correlation value data 275 (step B3). Then, the satellite signal acquisition unit 251 calculates the increased correlation value by multiplying the correlation value for the accumulation time by n (n> 1), and stores it in the storage unit 27 as the increased correlation value data 276 (step B5).

  Next, the satellite signal acquisition unit 251 performs a fast Fourier transform (FFT) process on the increased correlation value data 276 (step B7). Since the processing related to the fast Fourier transform is conventionally known, detailed description thereof is omitted.

  When the FFT processing is performed to obtain the power spectrum in the frequency domain, the satellite signal acquisition unit 251 extracts the power value at the specific frequency set in step B1 and adds it to the power value at the frequency zero (0 Hz) (step B9). ). The satellite signal acquisition unit 251 sets the power value at the specific frequency 278 to “0” (step B11).

  Next, the satellite signal acquisition unit 251 performs inverse fast Fourier transform processing (IFFT processing) to reconstruct the correlation value (step B13). Since processing related to inverse fast Fourier transform is also well known in the art, detailed description thereof is omitted.

  After the inverse FFT process is performed and the correlation value is reconstructed, the satellite signal acquisition unit 251 accumulates the reconstructed correlation values for the accumulated time, and updates the accumulated correlation value data 277 in the storage unit 27 (step B15). . That is, the reconstructed correlation values for the accumulation time are integrated and added to the latest integrated correlation value.

  Next, the satellite signal acquisition unit 251 determines whether or not the correlation integration time 273 set in step A5 has elapsed (step B17), and if it has determined that it has not yet elapsed (step B17; No), Return to B3. If it is determined that the correlation integration time has elapsed (step B17; Yes), the first correlation process is terminated.

  Returning to the baseband processing of FIG. 5, after performing correlation processing, the satellite signal acquisition unit 251 performs peak detection on the accumulated correlation value data 277 in the storage unit 27 (step A13) and determines that no peak has been detected. If so (step A13; No), the phase of the replica code is changed (step A15), and the process returns to step A9.

  If it is determined that a peak has been detected (step A13; Yes), the satellite signal acquisition unit 251 shifts the processing to the next acquisition target satellite. Then, after performing the processing of steps A5 to A15 for all the capture target satellites, the processing of loop A is terminated (step A17).

  Thereafter, the position calculation unit 253 performs position calculation calculation using the GPS satellite signals captured for each capture target satellite (step A19). The position calculation calculation can be realized by performing a known convergence calculation using, for example, a least square method or a Kalman filter using a pseudo distance between the mobile phone 1 and each captured satellite.

  The pseudo distance can be calculated as follows. That is, the integer part of the pseudorange is calculated using the satellite position of the captured satellite obtained from the satellite orbit data 272 and the latest calculated position of the mobile phone 1. Further, the fractional portion of the pseudorange is calculated using the phase (code phase) of the replica code corresponding to the correlation value peak detected in step A13. The pseudo distance can be calculated by adding the integer part and the fractional part thus obtained.

  Next, the position calculation unit 253 outputs the calculated position (position coordinates) to the host CPU 30 (step A21). Then, the processing unit 25 determines whether or not to end the processing (step A23). If it is determined that the processing is not yet ended (step A23; No), the processing unit 25 returns to step A1. If it is determined that the process is to be terminated (step A23; Yes), the baseband process is terminated.

(2) Experimental Results The experimental results when a GPS satellite signal is captured will be described with reference to FIGS. FIGS. 10-12 is a figure which shows an example of the experimental result at the time of acquiring a GPS satellite signal according to the conventional signal acquisition method. For each of the frequency direction and the phase direction, an experiment was performed in which correlation values for 40 milliseconds were accumulated for 1 second to obtain an accumulated correlation value, and the peak was detected.

  FIG. 10 is a graph in which the integrated correlation values in the phase direction and the frequency direction are plotted three-dimensionally. In FIG. 10, the right depth direction shows the phase difference between the phase of the received CA code and the phase of the replica code, and the left depth direction shows the frequency difference between the frequency of the received signal and the frequency of the carrier removal signal. ing. The vertical axis indicates the integrated correlation value. Among the graphs in FIG. 10, a graph obtained by extracting the correlation processing result in the frequency direction is shown in FIG. 11, and a graph obtained by extracting the correlation processing result in the phase direction is shown in FIG.

  Referring to FIG. 12, regarding the correlation processing result in the phase direction, the peak of the integrated correlation value appears in the portion of the phase difference “0”, and it can be seen that the correct result is obtained. However, as shown in FIG. 11, regarding the correlation processing result in the frequency direction, the peak of the integrated correlation value does not appear in the portion of the frequency difference “0 Hz”, and the frequency difference slightly apart from “0 Hz” in the left and right directions. It can be seen that a peak appears. When the frequency difference at which this peak appeared was examined, it was found that it was a frequency difference corresponding to the specific frequency “± 25 Hz”. Since no peak appears in the frequency difference “0 Hz”, it means that acquisition of the GPS satellite signal has failed.

  FIGS. 13 to 15 are diagrams illustrating an example of experimental results when a GPS satellite signal is captured according to the signal capturing method of the first embodiment. For each of the frequency direction and the phase direction, assuming that the accumulation time is “40 milliseconds” and the correlation integration time is “1000 milliseconds”, the above-described first correlation process is performed to determine the integrated correlation value, and the peak is detected. The experiment was conducted.

  FIG. 13 is a graph in which the integrated correlation values in the phase direction and the frequency direction are plotted three-dimensionally. Further, among the graphs of FIG. 13, a graph obtained by extracting the correlation integration result in the frequency direction is shown in FIG. 14, and a graph obtained by extracting the correlation integration result in the phase direction is shown in FIG. The way of viewing the graph is the same as in FIGS.

  Referring to FIG. 15, regarding the correlation processing result in the phase direction, it can be seen that the peak of the integrated correlation value appears in the portion of the phase difference “0”, and the correct result is obtained. 14 that the peak of the integrated correlation value appears in the frequency difference “0 Hz” portion of the correlation processing result in the frequency direction. Since the phase and frequency are exactly the same, it means that the GPS satellite signal has been successfully acquired.

(3) Effect In the baseband processing circuit unit 20, the correlator 23 performs a correlation operation on the received signal received from the GPS satellite signal transmitted from the GPS satellite. Then, the processing unit 25 performs frequency analysis using Fourier transform on the correlation calculation result over a predetermined accumulation time equal to or longer than the bit length (20 milliseconds) of the navigation message data carried in the GPS satellite signal. . Then, the power value at the specific frequency (25 Hz) corresponding to the bit length of the navigation message data is added to the power value at the frequency zero, the power value at the specific frequency is set to “0”, and then the correlation value is obtained by inverse Fourier transform. Is reconstructed. Then, the reconstructed correlation value is integrated, and a GPS satellite signal is captured based on the integrated correlation value.

  When the bit value of the navigation message data changes (inverts), the polarity of the CA code is also inverted. Therefore, when correlation calculation with the replica CA code is performed, a code change appears in the time series data of the correlation value. Therefore, when Fourier transform is performed on time-series data of correlation values, as described in the principle, a peak of power value appears at a frequency (specific frequency) of “25 Hz”.

  The peak of the power value at the specific frequency is caused by a change in the bit value of the navigation message data. Therefore, a process of extracting the power value at the specific frequency and moving it to the power value at the frequency zero is performed. After performing such processing, by reconstructing the correlation value by inverse Fourier transform, it is possible to obtain time-series data of correlation values with the same code. If the correlation values with the same sign are integrated, the correlation values with different signs do not cancel each other. Accordingly, correlation processing over a correlation integration time longer than the bit length (20 milliseconds) of the navigation message data can be realized.

  In the present embodiment, the accumulation time for storing the correlation value in an accumulative manner is set as a time 1 / m times the correlation integration time. Then, an increased correlation value is calculated by multiplying the accumulated correlation value for the accumulation time by n, and Fourier transform is performed on the time-series data of the increased correlation value, thereby increasing the power spectral density and frequency analysis. Can improve the accuracy.

  As can be seen from the experimental results described above, when the acquisition of the GPS satellite signal fails, the peak of the integrated correlation value appears at the frequency difference corresponding to the specific frequency, and when the acquisition is successful, the integrated correlation value at the frequency difference zero. The peak appears. Considering this, it can be said that moving the power value at a specific frequency to the power value at zero frequency is detecting the reception frequency of a GPS satellite signal.

(4) Other Correlation Processing The first correlation processing described with reference to FIG. 6 is an example of correlation processing, and is not limited thereto. Another example of correlation processing will be described with reference to a flowchart. In the flowchart described below, the same steps as those in the first correlation process are denoted by the same reference numerals, and the description thereof is omitted. The steps different from those in the first correlation process are mainly described.

  FIG. 7 is a flowchart showing the flow of the second correlation process which is an example of another correlation process. In the second correlation process, after step B1, the satellite signal acquisition unit 251 sets the harmonic frequency 279 (step C2). As the harmonic frequency 279, for example, a frequency that is an odd multiple of the specific frequency 278 set in step B1 is set.

  Then, the satellite signal acquisition unit 251 performs the FFT process in Step B7, then extracts the power values at the specific frequency and the harmonic frequency and adds them to the power value at the frequency zero (Step C9). Further, the power value at the specific frequency and the harmonic frequency is set to “0” (step C11). The subsequent processing is the same as the first correlation processing.

  FIG. 8 is a flowchart showing a flow of third correlation processing which is an example of other correlation processing. In the third correlation processing, the satellite signal acquisition unit 251 adds the power value at the specific frequency to the power value at the frequency zero in Step B9, and then performs the inverse zero processing without using the inverse FFT processing as the correlation processing result. Update (step D13).

  In the subsequent processing, the satellite signal capturing unit 251 captures the GPS satellite signal by regarding the power value at the frequency zero as the correlation processing result. Note that in the third correlation process, a power value other than the power value at zero frequency is not necessary, so the step of setting the power value at the specific frequency in the first correlation process to “0” (step B11 in FIG. 6) is omitted. ing.

In this way, the reason why processing can be performed by regarding the power value at frequency zero as the correlation processing result will be described. When Fourier transform is performed using a computer (computer), discrete Fourier transform is generally used. The discrete Fourier transform for the correlation value is formulated by the following equation (1).

In Expression (1), “x _k ” indicates a correlation value, and the subscript “k” indicates a sampled correlation value number. “F _j ” represents a frequency, and the subscript “j = 0, 1, 2,..., N−1” represents a sampled frequency number.

In this case, the power value “Power _j ” for the j-th frequency is given by the following equation (2).

Further, the inverse Fourier transform from the frequency to the correlation value is formulated by the following equation (3).

In step B9 of the third correlation process, the power value at zero frequency obtained by adding the power value at the specific frequency to the power value at zero frequency (hereinafter referred to as “total frequency zero power value”) is “Power ′”. _In the case of “ ₀ ”, when the inverse Fourier transform is performed by paying attention only to the DC component, the following expression (4) is derived.

However, when the formula (4) is derived, the fact that the following formula (5) is established from the formula (2) is used.

When the accumulation time is “t”, the correlation value “x _k ” reconstructed by the inverse Fourier transform is accumulated for the accumulation time “t”, thereby obtaining an accumulated correlation value “X” as in the following equation (6). Is obtained.

Looking at Equation (6), the accumulated correlation value “X” for the accumulation time depends on the accumulation time “t”, the total frequency zero power value “Power ′ ₀ ”, and the total sampling number “n”. Recognize. Here, the accumulation time “t” and the total sampling number “n” are constants. Therefore, the integrated correlation value “X” can be obtained simply by multiplying the total frequency zero power value “Power ′ ₀ ” by a constant. From this, it can be said that the combined frequency zero power value is equivalent to the reconstructed correlation value. Therefore, the GPS satellite signal can be captured using the total frequency zero power value itself without performing the inverse Fourier transform.

  FIG. 9 is a flowchart showing the flow of a fourth correlation process which is an example of another correlation process. In the fourth correlation process, the satellite signal acquisition unit 251 performs the FFT process in Step B7, and then calculates the power value at the frequency zero and the power value at the specific frequency (Step E8). Then, the calculated power values are compared (step E9).

  When the power value at the specific frequency is larger (step E9; power value at the specific frequency), the satellite signal acquisition unit 251 performs the inverse FFT process after performing the processes of steps B9 and B11 (step B13). On the other hand, when the power value at the frequency zero is larger (step E9; power value at the frequency zero), the inverse FFT process is performed as it is.

  In the fourth correlation process, the process is changed depending on whether or not the bit of the navigation message data has been inverted within the accumulation time, and depending on the relative magnitude of the power value at the specific frequency when there is. .

  That is, if the power value at the specific frequency is larger than the power value at the zero frequency, it is determined that there is bit inversion within the accumulation time and the power value at the specific frequency is relatively large. In this case, the process is continued by adding the power value of the specific frequency to the power value of zero frequency. On the other hand, if the power value at the frequency zero is larger than the power value at the specific frequency, it is determined that the power value at the specific frequency is not relatively large or bit inversion has not occurred, and the power value is not moved. continue processing.

2-2. Second Embodiment In the second embodiment, a GPS satellite signal is captured based on an integrated correlation value obtained by performing correlation processing using wavelet transform, which is a type of frequency analysis, and integrating the reconstructed correlation values. This is an example.

(1) Process Flow FIG. 16 is a flowchart showing a fifth correlation process which is an example of a correlation process using wavelet transform.
First, the satellite signal acquisition unit 251 sets the specific frequency 278 and stores it in the storage unit 27 (step F1). The specific frequency 278 is set to “25 Hz” as described in the principle.

  Next, the satellite signal acquisition unit 251 accumulates the correlation value output from the correlator 23 for the accumulation time, and stores it in the storage unit 27 as the correlation value data 275 (step F3). Then, the satellite signal acquisition unit 251 calculates the increase correlation value by multiplying the correlation value for the accumulation time by n, and stores it in the storage unit 27 as the increase correlation value data 276 (step F5).

Thereafter, the satellite signal acquisition unit 251 calculates the wavelet scale “a” according to the following equation (7) using the specific frequency set in step F1 as a pseudo frequency (step F7).

In Expression (7), “F _a ” and “F _c ” indicate the pseudo frequency and the center frequency of the wavelet function, respectively. “A” indicates a wavelet scale, and “dT” indicates a sampling period of the input signal.

Next, the satellite signal acquisition unit 251 uses the wavelet scale “a” calculated in step F7 to obtain a decomposition level “J” (hereinafter, “specific frequency decomposition level”) corresponding to a specific frequency according to the following equation (8). (Step F9).

  Next, the satellite signal acquisition unit 251 performs wavelet transform processing on the increased correlation value data 276 (step F13). The wavelet transform is a kind of linear filtering, and an input signal (here, time-series data of increased correlation values) is converted into a wavelet filter “h” corresponding to a high-pass filter and a scaling filter “g” corresponding to a low-pass filter. Using two types of filters, a high frequency detailed component and a low frequency approximate component are decomposed. Then, the approximate component is repeatedly decomposed until a predetermined decomposition level is reached, and the input signal is expressed using wavelet components having multiple resolutions.

Specifically, when the time-series increasing correlation value is “x (t)”, the number of levels to be decomposed is “J”, and the approximate component “x ₀ (t)” of the decomposition level “ ₀ ” is the decomposition level. When decomposing to “J-1”, the following equation (9) is obtained.

In Expression (9), “x _j (t)” indicates an approximate component at the decomposition level “j”, and “g _j (t)” indicates a detailed component at the decomposition level “j”. By substituting “x _J-1 (t)” into the expression of the next lower decomposition level “J-2”, “x _J-2 (t)” is obtained, and the obtained “x _J-2 (t)” Is substituted into the expression at the lower decomposition level “J-3” and “x _J−3 (t)” is obtained up to the decomposition level “0”. The increased correlation value “x (t)” is expressed.

  In this way, a method of expressing an input signal with the sum of wavelet components having different resolutions is called multi-resolution analysis. When realizing wavelet transformation using a computer (computer), discrete wavelet transformation that selects a scale parameter “a” based on the power of 2 is used in order to perform calculation more efficiently.

  After performing the wavelet transform process, the satellite signal acquisition unit 251 extracts the energy value of the high-frequency detailed component for the specific frequency decomposition level “J” and adds it to the energy value of the low-frequency approximate component (step F15). Further, the energy value of the high-frequency detailed component at the specific frequency decomposition level “J” is set to “0” (step F17). The energy value of the low-frequency approximate component is represented by the square value of the approximate component coefficient (scaling coefficient), and the energy value of the high-frequency detailed component is represented by the square value of the detailed component coefficient (wavelet coefficient).

  In addition, since the concept of “energy value” is generally used in wavelet transform, it is illustrated and described in this embodiment as processing that uses the concept of energy value. However, the energy value is still a kind of power value in frequency analysis, and is synonymous with the power value.

但し、「ｃＡ」は近似成分係数（スケーリング係数）を示し、「ｃＤ」は詳細成分係数（ウェーブレット係数）を示す。 In the discrete wavelet transform, since the increased correlation value “x (t)” is decomposed into an approximate component and a detailed component, the energy value of the increased correlation value “x (t)” is stored in the approximate component and the detailed component. Is done. That is, the law of energy conservation of the following expressions (11) and (12) is established.

However, “cA” indicates an approximate component coefficient (scaling coefficient), and “cD” indicates a detailed component coefficient (wavelet coefficient).

  In steps F15 and F17, for the specific frequency decomposition level “J”, the energy value of the high-frequency detailed component is extracted and added to the energy value of the low-frequency approximate component, and then the energy value of the high-frequency detailed component is set to “0”. It is carried out. Since the total amount of energy values does not change, the above-mentioned energy conservation law is satisfied in the processing of this embodiment.

  Thereafter, the satellite signal acquisition unit 251 performs inverse wavelet transform processing to reconstruct the increased correlation value (step F19). Then, the satellite signal acquisition unit 251 accumulates the correlation values for the reconstructed accumulation time, and updates the accumulated correlation value data 277 in the storage unit 27 (Step F21).

  Next, the satellite signal acquisition unit 251 determines whether or not the correlation integration time has elapsed (step F23). If it is determined that the correlation integration time has not yet elapsed (step F23; No), the process returns to step F3. If it is determined that the correlation integration time has elapsed (step F23; Yes), the fifth correlation process is terminated.

(2) Experimental Results Experimental results when a GPS satellite signal is captured using the method of the second embodiment will be described. Here, the result of performing correlation processing between the received CA code and the replica CA code with the frequency of the received signal and the phase of the received CA code as known is shown.

  FIG. 18 is a graph obtained by measuring the correlation value for 1000 milliseconds (1 second), and shows the time series change of the raw correlation value before performing the wavelet transform in the fifth correlation process described above. The horizontal axis represents time, and the vertical axis represents the correlation value. As shown in this figure, the sign of the correlation value changes in a short cycle due to the polarity of the received CA code being inverted by the change in the bit value of the navigation message data, and the positive and negative areas center around the correlation value “0”. It can be seen that it vibrates greatly. When this correlation value was integrated with the correlation integration time being 1000 milliseconds, the integration correlation value was “0”.

  FIG. 19 is a graph showing a time-series change in correlation values after the above-described fifth correlation process is performed on the correlation value data in FIG. 18 to reconstruct the signal. From this figure, it can be seen that the center of the correlation value is shifted to a positive region, and the correlation value is approximately within a positive value. Further, when attention is paid to the vertical vibration, it can be seen that although the pulse-like change is partially recognized, the fluctuation as a whole varies with a small amplitude. When this reconstructed correlation value was integrated with a correlation integration time of 1000 milliseconds, the integrated correlation value was a very large value of “680”.

(3) Other Correlation Processing The fifth correlation processing described with reference to FIG. 16 is an example of correlation processing using wavelet transform, and is not limited to this processing method. Another example of correlation processing will be described with reference to a flowchart. In the flowchart described below, steps that are the same as those in the fifth correlation process are denoted by the same reference numerals and description thereof is omitted, and steps different from those in the fifth correlation process are mainly described.

  FIG. 17 is a flowchart showing the flow of a sixth correlation process which is an example of another correlation process. In the sixth correlation process, the satellite signal acquisition unit 251 sets the harmonic frequency 279 after setting the specific frequency 278 in step F1 (step G2). The harmonic frequency is set to an odd multiple of the specific frequency.

  The satellite signal acquisition unit 251 determines the decomposition level (specific frequency decomposition level) “J” corresponding to the specific frequency according to the equation (8) using the wavelet scale “a” calculated in step F7 (step F9). . Further, a decomposition level corresponding to the harmonic frequency (hereinafter referred to as “harmonic frequency decomposition level”) is determined (step G11). That is, at a decomposition level lower than the specific frequency decomposition level “J”, a decomposition level corresponding to an odd multiple of the specific frequency is specified and determined as a harmonic frequency decomposition level.

  After performing the wavelet transform process in step F13, the satellite signal acquisition unit 251 extracts the energy value of the high-frequency detailed component and adds it to the energy value of the low-frequency approximate component for the specific frequency decomposition level and the harmonic frequency decomposition level. (Step G15). Further, the high frequency detailed component at the specific frequency resolution level and the harmonic frequency resolution level is set to “0” (step G17). And the satellite signal acquisition part 251 transfers a process to step F19.

  In the sixth correlation process, since the correlation value is reconstructed in consideration of not only the frequency component of the specific frequency but also the harmonic frequency component, the GPS satellite signal can be captured more accurately and quickly. .

  As in the third correlation process described in the modification of the first embodiment, the inverse wavelet transform is omitted, and the energy value of the low-frequency approximate component at the specific frequency decomposition level is regarded as the correlation process result and the GPS satellite. The signal may be captured.

3. Modification 3-1. Electronic Device In the above-described embodiments, the case where the present invention is applied to a mobile phone which is a kind of electronic device has been described as an example. However, an electronic device to which the present invention can be applied is not limited thereto. For example, the present invention can be similarly applied to other electronic devices such as a car navigation device, a portable navigation device, a personal computer, a PDA (Personal Digital Assistant), and a wristwatch.

3-2. In the above-described embodiment, the GPS has been described as an example of the position calculation system. However, WAAS (Wide Area Augmentation System), QZSS (Quasi Zenith Satellite System), GLONASS (GLObal NAvigation Satellite System), GALILEO It may be a position calculation system using other satellite positioning systems.

3-3. Extraction of Power Value In the above-described embodiment, it has been described that the power value at a specific frequency is extracted and added to the power value at the frequency zero. However, in practice, the power value may appear as an error component also in a frequency near the specific frequency. Therefore, it is preferable to perform processing with a specific frequency having a certain width.

  For example, the range of ± 1 Hz of the specific frequency is set as the specific frequency range, and all power values included in the specific frequency range are extracted and added to the power value at the frequency zero. In addition, all power values included in the specific frequency range are set to “0”. Then, after performing these processes, inverse frequency analysis is performed to reconstruct the correlation value.

  Note that the same processing may be performed not only for the specific frequency but also for the harmonic frequency. That is, the harmonic frequency has a certain width (for example, a harmonic frequency range of harmonic frequency ± 1 Hz), and the power value included in the harmonic frequency range is extracted and added to the power value at zero frequency. In addition, all power values included in the harmonic frequency range are set to “0”. Then, inverse frequency analysis is performed.

3-4. Increase correlation value In the above-described embodiment, the correlation value corresponding to the accumulation time is multiplied by n to calculate the increase correlation value, and the frequency analysis is performed on the time series data of the increase correlation value. However, this processing may be omitted, and frequency analysis may be performed on the correlation value data itself for the accumulation time.

  Instead of performing frequency analysis on the increased correlation value data, frequency analysis may be performed on data (sensitized correlation value data) in which the correlation value for the accumulation time repeats for a predetermined sensitization time. For example, a time that is k times the accumulation time (k> 1) is set as the sensitization time. Then, data in which the correlation value for the accumulation time is repeated for the sensitization time is generated as sensitization correlation value data, and the power spectrum is obtained by performing frequency analysis on the sensitization correlation value data.

3-5. Frequency analysis The frequency analysis is not limited to Fourier transform or wavelet transform. If the frequency component of the correlation value can be expressed by a power value, it goes without saying that the same effect as that of the above-described embodiment can be obtained by performing correlation processing using another frequency analysis.

DESCRIPTION OF SYMBOLS 1 Portable telephone, 10 GPS receiving part, 11 RF receiving circuit part, 20 Baseband processing circuit part, 21 Multiplier, 22 Carrier removal signal generation part, 23 Correlator, 24 Replica code generation part, 25 Processing part, 27 Storage unit, 30 host CPU, 40 operation unit, 50 display unit, 60 antenna for mobile phone, 70 wireless communication circuit unit for mobile phone, 80 storage unit

Claims (7)

Performing a correlation operation on a received signal received from a satellite signal transmitted from a positioning satellite;
Analyzing the frequency of the result of the correlation operation over a predetermined time longer than the bit length of the navigation message data carried by the satellite signal;
Of the results of the frequency analysis, and extracting the power value definitive of the bit length specified frequency to a half period,
And capturing the satellite signal using the extracted said power value,
A signal acquisition method comprising: Further comprising multiplying the result of the correlation operation over the predetermined time by n (n> 1),
The frequency analysis is performed on the result of the correlation operation multiplied by n.
The signal capturing method according to claim 1. The extracting is to extract the power value at the specific frequency and a harmonic of the specific frequency.
The signal acquisition method according to claim 1 or 2. Capturing the satellite signal, the extracted the power value is added to the power value in the zero frequency, comprising: performing the capturing using the power value after addition,
The signal acquisition method as described in any one of Claims 1-3. Capturing the satellite signal includes:
Adding the extracted power value to a power value at a frequency of zero , performing the inverse frequency analysis with the extracted power value being zero, and
Capturing the satellite signal using the result of the inverse frequency analysis;
including,
Signal acquisition method according to any one of claims 1-3. The frequency analysis is a frequency analysis using Fourier transform.
The signal capturing method according to claim 1. The frequency analysis is a frequency analysis using a wavelet transform.
The signal capturing method according to claim 1.

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